Now showing items 1-11 of 11

    • Explanation Ontology in Action: A Clinical Use-Case 

      Chari, Shruthi; Seneviratne, Oshani; Gruen, Daniel; Foreman, Morgan; Das, Amar; McGuinness, Deborah (2020-11-01)
      We addressed the problem of a lack of semantic representation for user-centric explanations and different explanation types in our Explanation Ontology (https://purl.org/heals/eo). Such a representation is increasingly ...
    • Explanation Ontology: A Model of Explanations for User-Centered AI 

      Chari, Shruthi; Seneviratne, Oshani; Gruen, Daniel; Foreman, Morgan; Das, Amar; McGuinness, Deborah (2020-11-01)
      Explainability has been a goal for Artificial Intelligence (AI) systems since their conception, with the need for explainability growing as more complex AI models are increasingly used in critical, high-stakes settings ...
    • FoodKG Enabled Questions and Answers Application 

      Haussmann, Steven; Chen, Yu; Seneviratne, Oshani; Rastogi, Nidhi; Codella, James; Chen, Ching Hua; McGuinness, Deborah; Zaki, Mohammed (2019-10-01)
      We demonstrate the usage of our FoodKG [3], a food knowledge graph designed to assist in food recommendation. This resource, which brings together recipes, nutrition, food taxonomies, and links into existing ontologies, ...
    • FoodKG: A Semantics-Driven Knowledge Graph for Food Recommendation 

      Haussmann, Steven; Seneviratne, Oshani; Chen, Yu; Ne'eman, Yarden; Codella, James; Chen, Ching Hua; McGuinness, Deborah; Zaki, Mohammed (2019-10-01)
      The proliferation of recipes and other food information on the Web presents an opportunity for discovering and organizing diet-related knowledge into a knowledge graph. Currently, there are several ontologies related to ...
    • Ingredient Substitutions Using a Knowledge Graph of Food 

      Shirai, Sola; Seneviratne, Oshani; Gordon, Minor; Chen, Ching Hua; McGuinness, Deborah (2021-01-25)
      People can affect change in their eating patterns by substituting ingredients in recipes. Such substitutions may be motivated by specific goals, like modifying the intake of a specific nutrient or avoiding a particular ...
    • Knowledge Integration for Disease Characterization: A Breast Cancer Example 

      Seneviratne, Oshani; Rashid, Sabbir; Chari, Shruthi; Bennett, Kristin; Hendler, Jim; McGuinness, Deborah (2018-07-20)
      With the rapid advancements in cancer research, the information that is useful for characterizing disease, staging tumors, and creating treatment and survivorship plans has been changing at a pace that creates challenges ...
    • Ontology-enabled Analysis of Study Populations 

      Chari, Shruthi; Qim, Miao; Agu, Nkechinyere; Seneviratne, Oshani; McCusker, Jamie; Bennett, Kristin; Das, Amar; McGuinness, Deborah (2019-10-01)
      We address the problem of modeling study populations in research studies in a declarative manner. Research studies often have a great degree of variability in the reporting of population descriptions. To make study populations ...
    • Ontology-enabled Breast Cancer Characterization 

      Seneviratne, Oshani; Rashid, Sabbir; Chari, Shruthi; McCusker, Jamie; Bennett, Kristin; Hendler, Jim; McGuinness, Deborah (2018-10-01)
      We address the problem of characterizing breast cancer, which today is done using staging guidelines. Our demo will show different breast cancer staging results that leverage the Whyis semantic nanopublication knowledge ...
    • Semantic Modeling of Cohort Descriptions in Research Studies 

      Chari, Shruthi; Weerawarana, Rukmal; Seneviratne, Oshani; McCusker, Jamie; McGuinness, Deborah; Das, Amar (2018-10-29)
      Recommendations in ADA’s Standards of Medical Care in Diabetes guideline are supported by findings from scientific publications (primarily clinical trials and case studies). We propose an approach rooted in Information ...
    • Semantically-targeted analytics for reproducible scientific discovery 

      New, Alexander; Chari, Shruthi; Qim, Miao; Rashid, Sabbir; Erickson, John; McGuinness, Deborah; Bennett, Kristin (2019-05-13)
      We develop a semantics-driven, automated approach for dynamically performing rigorous scientific studies. This framework may be applied to a wide variety of data and study types; here, we demonstrate its suitability for ...
    • Semantics-Driven Ingredient Substitution in the FoodKG 

      Shirai, Sola; Seneviratne, Oshani; Gordon, Minor; Chen, Ching Hua; McGuinness, Deborah (2020-11-01)
      The proliferation of recipes and other food information on the Web presents an opportunity for discovering and organizing diet-related knowledge into a knowledge graph. Currently, there are several ontologies related to ...